G10 Q4 Research

• When to use a t-test

  • Only when comparing two groups
  • Assumes data is independent, normally distributed, and has similar variance
• Types of t-tests

  • Paired t-test (when groups come from a single population)
  • Independent t-test (when groups come from two different populations)
  • One-sample t-test (when comparing one group to a standard value)
• One-tailed vs two-tailed t-test

  One-tailed: to determine if one population mean is greater/less than the other

  Two-tailed: to determine if the two populations are different from one another
• Performing a t-test


  1. Calculate t-value using the t-test equation

  2. Compare calculated t-value to critical t-value

  3. If t-stat > t-crit, reject the null hypothesis
• 1. test equation

  Estimates the true difference between two group means using the ratio of the difference in group means over the pooled standard error of both groups
• Calculating pooled standard error


  Pooled standard deviation x square root of (1/n1 + 1/n2)

  Pooled standard deviation = square root of ((n1-1)x(s1)^2 + (n2-1)x(s2)^2) / (n1+n2-2)
• Reporting t-test results
• t-test

  • is a statistical test that is used to compare the means of two groups.
  • It is often used in hypothesis testing to determine whether a process or treatment actually has an effect on the population of interest, or whether two groups are different from one another.
• When to use t-test

  • only when comparing two groups
  • it assumes that your data are independent, normally distributed, and have similar amount of variance
• Paired t-test

  • If the groups come from a single population (e.g., measuring before and after an experimental treatment)
  • AKA within-subjects design
• Independent t-test

  • If the groups come from two different populations (e.g., two different species, or people from two separate cities), perform
  • AKA between-subjects design
• One-sample t-test

  • If there is one group being compared against a standard value (e.g., comparing the acidity of a liquid to a neutral pH of 7),
  • AKA within-subjects design
• whether the two populations are different from one another, perform a two-tailed t-test.
•  whether one population mean is greater than or less than the other, perform a one-tailed t-test.
• • The t test estimates the true difference between two group means using the ratio of the difference in group means over the pooled standard error of both groups
• • You can compare your calculated t value against the values in a critical value chart (e.g., Student’s t table) to determine whether your t value is greater than what would be expected by chance.
  • if t stat > t crit, then reject the H0
• • A larger t value shows that the difference between group means is greater than the pooled standard error, indicating a more significant difference between the groups.
• Reporting t-test results

  • include the t value, p value, and degrees of freedom
  • you may also include the mean and standard deviation of the groups being compared
• RESULTS

  This is where you report the results of any statistical analysis procedures that you undertook.
• RESULTS

  The main results to report include:

  • any descriptive statistics
  • statistical test results
  • significance test results
  • estimates of confidence intervals
• WRITING RESULTS

  • text for highlighting few key results
  • large sets of data using tables or graphs
• WRITING RESULTS

  • include sample calculations for complex experiments
  • provide a brief description of what it does and use clear symbols
• • raw data should be in the Appendices section
  • you just need to “refer it” to highlight any outliers or trends
• DISCUSSION

  This is the section of your paper that will help demonstrate your understanding of the experimental process
• In this section you can:

  • interpret results
  • compare findings with your expectations
  • identify any sources of experimental error
  • explain any unexpected results
  • suggest possible improvements for further studies
• The results chapter or section simply and objectively reports what you found, without speculating on why you found these results.
• The discussion interprets the meaning of the results, puts them in context, and explains why they matter.
• Raw Data

  • save the raw data securely and make them available and accessible to any other researchers who request them
• Interpretation of results

  • you should state whether the findings of statistical tests lend support to your hypotheses
  • refrain from concluding about your RQs in the results section
• CONCLUSION

  This is the final section of your research paper. Here, you will summarize the findings of your experiment, with a brief overview of the strengths and limitations, and implications of your study for future research.
• To present three or fewer numbers, try a sentence
• To present between 4 and 20 numbers, try a table
• To present more than 20 numbers, try a figure
• Tables and Figures

  •Should be numbered

  •Have titles

  •With relevant notes

  •Present data only once throughout the paper and refer to any tables and figures in the text
• Table •concisely presents information (often numbers) in rows and columns
• Figure

  •any other image or illustration you include in your text—anything from a bar chart to a photograph
• • use a table or figure when it’s a clearer way to present important data than describing it in your main text
• Analysis of Variance

  to analyze the diff between means of more than two groups
• One-way anova

  • one IV
• Two-way anova

  • two IV